We present an information-theoretic approach to discrete signal processing called information-optimum signal processing for the example of a wireless receiver comprising LDPC decoding, channel estimation and detection. All operations are replaced by simple lookup tables and all messages which are exchanged between detection stages are unsigned integers. The lookup tables are designed offline using the information bottleneck concept of preserving relevant information. We show that the approach allows for simple signal processing with coarse quantization while achieving virtually the same performance as conventional signal processing approaches with high resolution, e.g. double precision. The contribution of the paper is a tutorial style explanation of the concept as well as an exemplary survey of applications and performance results which illustrate the potential of the concept.


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    Title :

    Information-Optimum Discrete Signal Processing for Detection and Decoding - Invited Paper


    Contributors:


    Publication date :

    2018-06-01


    Size :

    1117960 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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